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This article addresses the logical problem of language evolution that arises from a conventional universal grammar (UG) perspective and investigates the biological and cognitive constraints that are considered when explaining the cultural evolution of language. The UG prespective states that language acquisition should not be viewed as a process of learning at all but it should be viewed as a process of growth, analogous to the growth of the arm or the liver. UG is intended to characterize a set of universal grammatical principles that hold across all languages. Language has the same status...

This article addresses the logical problem of language evolution that arises from a conventional universal grammar (UG) perspective and investigates the biological and cognitive constraints that are considered when explaining the cultural evolution of language. The UG prespective states that language acquisition should not be viewed as a process of learning at all but it should be viewed as a process of growth, analogous to the growth of the arm or the liver. UG is intended to characterize a set of universal grammatical principles that hold across all languages. Language has the same status as other cultural products, such as styles of dress, art, music, social structure, moral codes, or patterns of religious beliefs. Language may be particularly central to culture and act as the primary vehicle through which much other cultural information is transmitted. The biological and cognitive constraints helps to determine which types of linguistic structure tend to be learned, processed, and hence transmitted from person to person, and from generation to generation. The communicative function of language is likely to shape language structure in relation to the thoughts that are transmitted and regarding the processes of pragmatic interpretation that people use to understand each other's behavior. A source of constraints derives from the nature of cognitive architecture, including learning, processing, and memory. The language processing involves generating and decoding regularities from highly complex sequential input, indicating a connection between general-purpose cognitive mechanisms for learning and processing sequential material, and the structure of natural language.